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Compressing DNNs is important for the real-world applications operating on resource-constrained devices.
On the best rank-1 and rank-( r 1 , r 2 , … , r n r_{1},r_{2},\ldots,r_{n} ) approximation of higher-order tensors
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Compression of deep convolutional neural networks for fast and low power mobile applications
Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, and Dongjun Shin · 2016
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Learning efficient convolutional networks through network slimming
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